Mixtral 8x22B Instruct vs Mistral Large 2.1
Mistral Large 2.1 comes out ahead, 38 to 34 on our weighted score.
Mistral AIMixtral 8x22B Instruct
34/100- ECI122.0
- Price$2.00 / $6.00
- Context66K
- Our pickMistral AI
Mistral Large 2.1
38/100- ECI128.6
- Price$2.00 / $6.00
- Context131K
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Mistral Large 2.1 is our pick
Mistral Large 2.1 is the better all-round choice, scoring 38/100 against Mixtral 8x22B Instruct (34). It leads on capability and context window. Mixtral 8x22B Instruct wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.6 · Mixtral 8x22B Instruct 122.0
- Lowest priceSame priceMixtral 8x22B Instruct $3.00 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2.1Mistral Large 2.1 131,072 · Mixtral 8x22B Instruct 65,536 tokens
- Widest inputsMixtral 8x22B InstructMixtral 8x22B Instruct: Text, PDFs · Mistral Large 2.1: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mixtral 8x22B Instruct | Mistral Large 2.1 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 42 | 50 |
| Price | 25% | 26 | 26 |
| Inputs & features | 15% | 35 | 25 |
| Context window | 10% | 12 | 25 |
| Overall | 100% | 34/100 | 38/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mixtral 8x22B InstructMistral AI | Mistral Large 2.1Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 122.0 | 128.6 (best) |
| ECI rank | #155 of 165 | #142 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 34.1% | 51.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.8% |
| Price per million tokens | ||
| Input | $2.00 | $2.00 |
| Output | $6.00 | $6.00 |
| Cached input | — | — |
| Blended (3:1) | $3.00 | $3.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 5 providers | Median of 2 providers |
| Limits | ||
| Context window | 65,536 tokens | 131,072 tokens (best) |
| Max output | 52,428 tokens (best) | 16,384 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | — |
| API providers | 5 (best) | 2 |
| Released | Apr 17, 2024 | Nov 18, 2024 |
| Knowledge cutoff | Jan 31, 2024 | Nov 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mixtral 8x22B Instruct$32.00
- Mistral Large 2.1$32.00
Which should you choose?
Which is better: Mixtral 8x22B Instruct or Mistral Large 2.1?
Mistral Large 2.1 is the better all-round choice, scoring 38/100 against Mixtral 8x22B Instruct (34). It leads on capability and context window. Mixtral 8x22B Instruct wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mixtral 8x22B Instruct or Mistral Large 2.1?
Mixtral 8x22B Instruct and Mistral Large 2.1 cost the same: $2.00 input / $6.00 output per million tokens.
Which scores higher on benchmarks?
Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.6 (#142 of 165) and Mixtral 8x22B Instruct 122.0 (#155 of 165). The confidence ranges of the top two overlap (124.3–130.7 vs 115.7–124.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Mixtral 8x22B Instruct 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Mixtral 8x22B Instruct and Mistral Large 2.1 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Large 2.1 has the largest context window at 131,072 tokens, against 65,536 for Mixtral 8x22B Instruct. Maximum output per response: Mixtral 8x22B Instruct up to 52,428, Mistral Large 2.1 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Mixtral 8x22B Instruct accepts text and PDFs; Mistral Large 2.1 accepts text. Mixtral 8x22B Instruct handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Mistral Large 2.1 is the newest, released Nov 18, 2024. Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Mixtral 8x22B Instruct Jan 31, 2024, Mistral Large 2.1 Nov 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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